A physically based model for preferential water flow and solute transport in drained agricultural fields

Author(s):  
M. Holbak ◽  
P. Abrahamsen ◽  
S. Hansen ◽  
E. Diamantopoulos
2021 ◽  
Author(s):  
Efstathios Diamantopoulos ◽  
Maja Holbak ◽  
Per Abrahamsen

<p>Preferential water flow and solute transport in agricultural systems affects not only the quality of groundwater but also the quality of surface waters like streams and lakes. This is due to the rapid transport of agrochemicals, immediately after application, through subsurface drainpipes and surface water. Experimental evidence attributes this to the occurrence of continuously connected pathways, connecting the soil surface directly with the drainpipes. We developed a physically-based model describing preferential flow and transport in biopores and implemented it in the agroecological model Daisy. The model simulates the often observed rapid transport of chemicals from   the upper soil layers to the drainpipes or to deeper layers of the soil matrix. Based on field investigations, biopores with specific characteristics can be parameterized as classes with different vertical and horizontal distributions. The model was tested against experimental data from a column experiment with an artificial biopore and showed good results in simulating preferential flow dynamics. We illustrate the performance of the new approach, by conducting five simulations assuming a two-dimensional simulation domain with different biopore parametrizations, from none to several different classes. The simulation results agreed with experimental observations reported in the literature, indicating rapid transport from the soil to the drainpipes. Furthermore, the different biopore parametrizations resulted in distinctly different leaching patterns, raising the expectation that biopore properties could be estimated or constrained based on observed leaching data and direct measurements.</p>


2015 ◽  
Vol 14 (9) ◽  
pp. vzj2015.02.0021 ◽  
Author(s):  
Antonio Coppola ◽  
Alessandro Comegna ◽  
Giovanna Dragonetti ◽  
Horst H. Gerke ◽  
Angelo Basile

2009 ◽  
Vol 104 (1-4) ◽  
pp. 74-83 ◽  
Author(s):  
Antonio Coppola ◽  
Vincenzo Comegna ◽  
Angelo Basile ◽  
Nicola Lamaddalena ◽  
Gerardo Severino

2019 ◽  
Vol 19 (11) ◽  
pp. 2477-2495
Author(s):  
Ronda Strauch ◽  
Erkan Istanbulluoglu ◽  
Jon Riedel

Abstract. We developed a new approach for mapping landslide hazards by combining probabilities of landslide impacts derived from a data-driven statistical approach and a physically based model of shallow landsliding. Our statistical approach integrates the influence of seven site attributes (SAs) on observed landslides using a frequency ratio (FR) method. Influential attributes and resulting susceptibility maps depend on the observations of landslides considered: all types of landslides, debris avalanches only, or source areas of debris avalanches. These observational datasets reflect the detection of different landslide processes or components, which relate to different landslide-inducing factors. For each landslide dataset, a stability index (SI) is calculated as a multiplicative result of the frequency ratios for all attributes and is mapped across our study domain in the North Cascades National Park Complex (NOCA), Washington, USA. A continuous function is developed to relate local SI values to landslide probability based on a ratio of landslide and non-landslide grid cells. The empirical model probability derived from the debris avalanche source area dataset is combined probabilistically with a previously developed physically based probabilistic model. A two-dimensional binning method employs empirical and physically based probabilities as indices and calculates a joint probability of landsliding at the intersections of probability bins. A ratio of the joint probability and the physically based model bin probability is used as a weight to adjust the original physically based probability at each grid cell given empirical evidence. The resulting integrated probability of landslide initiation hazard includes mechanisms not captured by the infinite-slope stability model alone. Improvements in distinguishing potentially unstable areas with the proposed integrated model are statistically quantified. We provide multiple landslide hazard maps that land managers can use for planning and decision-making, as well as for educating the public about hazards from landslides in this remote high-relief terrain.


Author(s):  
Abderrazzak El Boukili

Purpose – The purpose of this paper is to provide a new three dimension physically based model to calculate the initial stress in silicon germanium (SiGe) film due to thermal mismatch after deposition. We should note that there are many other sources of initial stress in SiGe films or in the substrate. Here, the author is focussing only on how to model the initial stress arising from thermal mismatch in SiGe film. The author uses this initial stress to calculate numerically the resulting extrinsic stress distribution in a nanoscale PMOS transistor. This extrinsic stress is used by industrials and manufacturers as Intel or IBM to boost the performances of the nanoscale PMOS and NMOS transistors. It is now admitted that compressive stress enhances the mobility of holes and tensile stress enhances the mobility of electrons in the channel. Design/methodology/approach – During thermal processing, thin film materials like polysilicon, silicon nitride, silicon dioxide, or SiGe expand or contract at different rates compared to the silicon substrate according to their thermal expansion coefficients. The author defines the thermal expansion coefficient as the rate of change of strain with respect to temperature. Findings – Several numerical experiments have been used for different temperatures ranging from 30 to 1,000°C. These experiments did show that the temperature affects strongly the extrinsic stress in the channel of a 45 nm PMOS transistor. On the other hand, the author has compared the extrinsic stress due to lattice mismatch with the extrinsic stress due to thermal mismatch. The author found that these two types of stress have the same order (see the numerical results on Figures 4 and 12). And, these are great findings for semiconductor industry. Practical implications – Front-end process induced extrinsic stress is used by manufacturers of nanoscale transistors as the new scaling vector for the 90 nm node technology and below. The extrinsic stress has the advantage of improving the performances of PMOSFETs and NMOSFETs transistors by enhancing mobility. This mobility enhancement fundamentally results from alteration of electronic band structure of silicon due to extrinsic stress. Then, the results are of great importance to manufacturers and industrials. The evidence is that these results show that the extrinsic stress in the channel depends also on the thermal mismatch between materials and not only on the material mismatch. Originality/value – The model the author is proposing to calculate the initial stress due to thermal mismatch is novel and original. The author validated the values of the initial stress with those obtained by experiments in Al-Bayati et al. (2005). Using the uniaxial stress generation technique of Intel (see Figure 2). Al-Bayati et al. (2005) found experimentally that for 17 percent germanium concentration, a compressive initial stress of 1.4 GPa is generated inside the SiGe layer.


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